Several improvements are on the horizon, which will add powerful optimization capabilities into the process modeler’s simulation work space in areas like heat integration, column optimization and economics.

Refining operations continue to be a crucial but challenging
element in the petroleum value chain; critical to the ability
to bring hydrocarbons to market, but, in many instances, still
a challenge in terms of attaining targeted levels of
profitability. Fortunately, there have been rapid innovations
and advances in several of the key enabling modeling
technologies that contribute to the ability to react to
technical and business changes. There are more innovations on
the horizon. Refinery assets and operations are in the midst of
an evolution, both in terms of the worldwide distribution and
age of refining capacity, and the demand
for flexibility in crude selection and product portfolios.

Software innovations discussed here fall into four general
groups. One area of innovation is the workflow and usability of
sophisticated refinery modeling tools. Increasingly,
high-fidelity models are being used for refinery operation, planning, maintenance, cost feasibility and
troubleshooting. The importance of these developments cannot be
understated as a new generation of engineers enters the
workforce.

A second area involves breakthroughs in the integration of models that enable
optimization and improvement on a refinery-wide basis, such as
heat integration, energy savings and
capacity improvement. A third area involves advances in
underlying science and methods, including improved molecular
modeling and better statistical models to characterize and
represent properties of crude oil, and transparent reactor
models that provide rapid updating of planning models. A final
and increasingly important advance encompasses new usability
paradigms that provide mobile access to all plant models and
data anytime, anywhere.

The business result of the above advances is a significantly
improved ability of the organization to respond to crude
selection and product contract opportunities, reduction in
energy consumption, and improved sustainability and control. These
are the requirements of the next generation of refineries.

Faster training

Process modeling systems that can represent, characterize,
model and optimize refineries involve considerable complexity
of functionality, tools, options and reporting capabilities. As
the functionality of these models increased over the past 15
years, the usability of the modeling systems did not improve at
a parallel pace, and, in many cases, it became problematic.

Over the past year, in-depth analyses of how a modeler
builds and employs a refinery simulation model has led to more
easily accessed models, more easily understood interfaces and
improved workflows.1Fig. 1 shows a
stylized program ribbon as implemented for properties analysis
and for simulation modeling.

High-fidelity exchanger models

Refineries have an ongoing focus on reducing their energy
footprint by optimizing energy use through operating,
equipment, maintenance and
process-configuration strategies. The use of more rigorous
models for heat exchangers, and the embedding of those models
within the refining simulation model, have
proven to be an important step for making refineries more
energy efficient. By modeling heat exchangers more accurately,
process design optimization can be less conservative, making
the process more profitable. Early identification of structural
challenges, such as vibration or fluid momentum (Rho
V2) problems, means a shorter cycle from conception
to feed.

Rigorous models also calculate pressure drops that help
design related equipment, such as pumps. These rigorous
modeling results are used to plan the upgrading or
reconfiguring of heat exchangers as a method of utilizing
energy more efficiently and to ensure that the selected
exchanger configurations are optimal for the conditions under
which they will operate.

A full geometric predesign of heat exchangers and
incorporation of the exchanger in the simulation is now
possible. This has resulted in engineers, equipment designers
and operators having early and greater fidelity in examining
the impact of design and operations decisions on heat use in
the plant.

Another important aspect of heat exchanger design that
relates to energy efficiency, as well as to efficient
operation, is equipment fouling. Rigorous heat exchanger models
can be used to calculate fouling resistance. This provides
operating benefits because, as fouling increases, equipment
throughput sharply decreases, creating serious efficiency
issues, as shown in Fig. 2.

Fig. 2. Example of
impact of fouling on refinery
furnace systems.

This heat exchanger modeling for fouling was used by a major
chemicals producer and refiner when modeling a heat exchanger
train. The refinery was experiencing significant increases in
operating costs because of heat exchanger fouling. The lack of
a rigorous model meant that the refiner was unable to
accurately calculate the fouling of single exchangers, as well
as the entire train, and it had no means to estimate output
temperature increases after the train was cleaned. With a
rigorous model, the company was able to accurately model the
fouling and determine how often the heat exchangers needed to
be cleaned for optimal operation. The profit resulting from
those improvements alone is estimated at between $1.5 million
(MM)/yr and $2 MM/yr.2

Molecular modeling and assay

In most geographies, the selection of crude oils available
as refinery inputs has widened, introducing more operating
choices. Crude oils are complex mixtures, and, depending on
where the crude is sourced, they can vary greatly in
composition. Due to the large number of different hydrocarbon molecules that can be present
in petroleum, it is infeasible to fully define the composition
of the mixture. However, each crude oil type has unique
molecular and chemical characteristics, so an assay is used to
evaluate the properties of the petroleum and obtain data to
characterize crude oil feeds. By characterizing these assays,
refiners can see whether a specific crude oil feedstock is compatible with a
particular petroleum refinery or if it will cause quality,
yield, economic or environmental issues.

Evaluations are costly and tedious, and they result in a
limited set of property measurements for the crude. Thus,
statistical extrapolation and interpolation, as well as
estimation methods, are used to predict missing properties for
refinery planning and process
simulation.

These statistical methods have been used extensively in the
industry, but the limited assay data makes precise fitting
difficult, which can result in incorrect characterizations that
will impact the accuracy of the model. Modelers must take
advantage of special factors or handles provided by traditional
assay characterization tools to ensure that the results are
correct and lead to realistic modeling outcomes. Recent
research has focused on improving such tools to more fully
incorporate the engineering knowledge of the problem, with the
goal of better results.

Traditional analytical approaches suffer from extrapolation
limitations, depending on the assay data available. With the
selection of crudes on the market becoming heavier, the need
for a new and fundamentally better methodology for crude assays
is more important than ever.

An exciting new innovation, molecule-based characterization,
offers the strongest scientific basis for the prediction of
crude oil properties, as it bases its calculations on the
chemical compositions of the hydrocarbon constituent molecules
and on accurate molecular thermodynamic models for hydrocarbon
mixtures.3

This approach to crude characterization has, as a basis, the
principle that all hydrocarbon molecules can be constructed
from a set of different structural segments, which can be
described as a specific structural combination of carbon, hydrogen, sulfur, nitrogen
and oxygen atoms. By modeling the complex hydrocarbons in the
crude oil as a series of repeating molecular segments, the
assay characterization has significantly improved accuracy,
especially for heavier and increasingly varied crudes, such as
high-sulfur oil. Refiners and planners are better able to
estimate the properties of the crude oil feedstock, which results in more
accurate reaction modeling.

Furthermore, using the same, improved assay characterization
method for both the simulation model of the refinery and
reactors, and the planning model for refinery operations, leads
to overall improvements in the ability to make economically
optimized decisions and to successfully predict refinery
conditions and performance.

High-fidelity reactor models

The improvements seen in modeling software in recent years
have been especially remarkable in the reactor design area.
These rigorous reactor models have accounted for significantly
more accurate determinations of equipment operations and easier
identification of possible optimizations.

In addition, whereas before it was necessary to model these
reactors separately and modify connecting streams by hand, it
is now possible to model them in one integrated
flowsheet.4 This advancement has become more
significant as more reactors are added to refineries, since it
enables modeling of the interactions between reactors to better
understand and optimize the process.

The increase in the number of reactors is due primarily to
the availability of heavier crudes. To keep up with this trend,
modeling software has focused on expanding the properties
available to model heavy crudes and, therefore, improve their
reaction modeling, as mentioned in the previous section.

To make the use of heavier crudes more economically
feasible, refineries have been adding cracking units to break
the heavier crudes into simpler hydrocarbons to obtain the
desired product blends. These sophisticated and vital cracking
units must be rigorously modeled to serve this purpose, which
increases the need for rigorous modeling software that can
perform within the context of a wider simulation model.

The trend toward adding reactors is seen, for example, in
Royal Dutch Shell adding hydrocrackers to three refineries in
Holland, China and Poland. In all three cases, the
hydrocrackers were added to take advantage of heavier crudes,
which are more economical than lighter crudes.5
Modeling these hydrocrackers is extremely important for making
this process feasible and will become more so, as more of these
units are added to refineries.

Planning model

Another important development in refinery modeling involves
advances in the ability of integrated software to update widely
used refinery planning models more accurately, more frequently
and with less specialized expertise.6 Support for
this activity within the newest releases of refinery simulation
models leads to better accuracy in the planning model for
feedstock selection. The automation and demystifying of these
interfaces is increasingly important as the addition of
reactors increases the complexity of the process.

With the ability to model how reactors influence the end
product, modeling software can interface with planning software
to assist in the selection of the best feedstock for the desired products.
Since the reactors involved in the process need to be
rigorously modeled to give an accurate result, it is crucial to
have planning software that can interface with the modeling
software to give the most accurate results possible. The result
is optimized reactor operating conditions and product output.
In the past, this activity always required a heavy dose of
expert consulting input, the resources for which were not
always available; however, that is no longer the case.

Mobile interfaces to refinery models

With the advent of mobile technology and the increasing number
of users of portable devices, it seems logical for refining and
engineering companies to take advantage of these new
capabilities to maximize productivity. By introducing
applications that allow users to access process charts and data
securely, without having to be onsite and without having to be
experts in the underlying tools and models, managers and
engineers can instantly receive updates and access models to
keep track of plants wherever they are located (Fig.
3).

The ability to manage various processes from any location can
help companies substantially reduce costs, while also
increasing flexibility and worker efficiency. With the
popularity of tablets and smartphones on the mobile devices
market, these applications can take advantage of the
convenience of monitoring ongoing activities at the plant from
anywhere.

Additionally, these devices have the added benefit of being
always on, always with the user and usually connected to a
global network. By providing a mobile interface for engineering
applications, users will rarely be in a position where they
will not be able to access data securely and instantly. This
key innovation ensures that companies keep up with, and take
full advantage of, modern shifts in technology.

More innovations to come

The innovations described here have largely been introduced
over the past two years, greatly accelerating the pace of
innovation and modeling power for refinery operations,
improvements and design. This pace of innovation is unlikely to
slow down. A number of exciting improvements are on the
horizon, which will add powerful optimization capabilities into
the process modelers simulation work space in areas such
as heat integration, column optimization and
economics.

Additionally, the refinery manager can expect important
advances in the power and value of mobile interfaces to give
the manager access to key refinery performance information,
anywhere and anytime, and to give the engineer access to the
technical details required to make improvements to the
performance. HP

Ron Beck
is the engineering product marketing director for Aspen
Technology, covering the aspenONE engineering suite. He
has worked for AspenTech for five years and is the
marketing manager for aspenONE Engineering. Mr. Beck
spent 10 years in a research and development organization
commercializing fluidized bed technologies, enhanced oil
recovery methods and environmental technology. He
has 20 years of experience in the development, adoption
and marketing of software solutions for engineering and
plant management. Mr. Beck has been involved with the
development of integrated solutions for several global
chemical enterprises. At AspenTech, he has also been
involved with AspenTechs economic evaluation
products. Mr. Beck is a graduate of Princeton University
in New Jersey.

Dinu
Ajikutira is Aspen Technologys senior
product manager for the Aspen HYSYS family of process
optimization products for the energy industry. He has
worked with Aspen Technology for nearly seven years, in
both product management and research and development.
Prior to working at AspenTech, he developed modeling technology for the process
industries and also worked on the plant floor. Mr.
Ajikutira is a chemical engineer with an MS degree from
the University of British Columbia in Canada.

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